Sigma Spikes [CC]Sigma Spikes were created by Adam Grimes and this is one of the best volatility indicators out there. This indicator not only gives you positive or negative volatility but with my version I can identify any sudden changes from the underlying trend. Buy when the line turns green and sell when it turns red.
Let me know if there were any other indicators you wanted to see me publish!
חפש סקריפטים עבור "Volatility"
ATR with MAOVERVIEW
The Average True Range Moving Average (ATRMA) is a technical indicator that gauges the amount of volatility currently present in the market, relative to the historical average volatility that was present before. It adds a moving average to the Average True Range (ATR) indicator.
This indicator is extremely similar to the VOXI indicator, but instead of measuring volume, it measures volatility. Volume measures the amount of shares/lots/units/contracts exchanged per unit of time. Volatility, on the other hand, measures the range of price movement per unit of time.
The purpose of this indicator is to help traders filter between non-volatile periods in the market from volatile periods in the market without introducing subjectivity. It can also help long-term investors to determine market regime using volatility without introducing subjectivity.
CONCEPTS
This indicator assumes that trends are more likely to start during periods of high volatility, and consolidation is more likely to persist during periods of low volatility. The indicator also assumes that the average true range (ATR) of the last 14 candles is reflective of the current volatility in the market. ATR is the average height of all the candles, where height = |high - low|.
Suppose the ATR of the last 14 candles is greater than a moving average of the ATR(14) of the last 20 candles (this occurs whenever the indicator's filled region is colored BLUE). In that case, we can assume that the current volatility in the market is high.
Suppose the ATR of the last 14 candles is less than the moving average of the ATR(14) of the last 20 candles (this occurs whenever the indicator's filled region is colored RED). In that case, we can assume that the current volatility in the market is low.
HOW DO I READ THIS INDICATOR?
If the ATR line is above the ATR MA line (indicated by the blue color), the current volatility is greater than the historical average volatility.
If the ATR line is above the ATR MA line (indicated by the red color), the current volatility is less than the historical average volatility.
VIX-Price Covariance MonitorThe VIX-Price Covariance Monitor is a statistical tool that measures the evolving relationship between a security's price and volatility indices such as the VIX (or VVIX).
It can give indication of potential market reversal, as typically, volatility and the VIX increase before markets turn red,
This indicator calculates the Pearson correlation coefficient using the formula:
ρ(X,Y) = cov(X,Y) / (σₓ × σᵧ)
Where:
ρ is the correlation coefficient
cov(X,Y) is the covariance between price and the volatility index
σₓ and σᵧ are the standard deviations of price and the volatility index
Enjoy!
Features
Dual Correlation Periods: Analyze both short-term and long-term correlation trends simultaneously
Adaptive Color Coding: Correlation strength is visually represented through color intensity
Market Condition Assessment: Automatic interpretation of correlation values into actionable market insights
Leading/Lagging Analysis: Optional time-shift analysis to detect predictive relationships
Detailed Information Panel: Real-time statistics including current correlation values, historical averages, and trading implications
Interpretation
Positive Correlation (Red): Typically bearish for price, as rising VIX correlates with falling markets. This is what traders should be looking for.
Negative Correlation (Green): Typically bullish for price, as falling VIX correlates with rising markets
How to use it
Apply the indicator to any chart to see its correlation with the default VIX index
Adjust the correlation length to match your trading timeframe (shorter for day trading, longer for swing trading)
Enable the secondary correlation period to compare different timeframes simultaneously
For advanced analysis, enable the Leading/Lagging feature to detect if VIX changes precede or follow price movements
Use the information panel to quickly assess the current market condition and potential trading implications
Contraction & Expansion Multi-Screener █ Overview:
The Contraction & Expansion Multi-Screener analyzes market volatility across many symbols. It provides insights into whether a market is contracting or expanding in volatility. With using a range of statistical models for modeling realized volatility, the script calculates, ranks, and monitors the degree of contraction or expansions in market volatility. The objective is to provide actionable insights into the current market phases by using historical data to model current volatility conditions.
This indicator accomplishes this by aggregating a variety of volatility measures, computing ranks, and applying threshold-based methods to identify transitions in market behavior. Volatility itself helps you understand if the market is moving a lot. High volatility or volatility that is increasing over time, means that the price is moving a lot. Volatility also mean reverts so if its extremely low, you can eventually expect it to return to its expected value, meaning there will be bigger price moves, and vice versa.
█ Features of the Indicator
This indicator allows the user to select up to 14 different symbols and retrieve their price data. There is five different types of volatility models that you can choose from in the settings of this indicator for how to use the screener.
Volatility Settings:
Standard Deviation
Relative Standard Deviation
Mean Absolute Deviation
Exponentially Weighted Moving Average (EWMA)
Average True Range (ATR)
Standard Deviation, Mean Absolute Deviation, and EWMA use returns to model the volatility, meanwhile Relative Standard Deviation uses price instead due to its geometric properties, and Average True Range for capturing the absolute movement in price. In this indicator the volatility is ranked, so if the volatility is at 0 or near 0 then it is contracting and the volatility is low. If the volatility is near 100 or at 100 then the volatility is at its maximum.
For traders that use the Forex Master Pattern Indicator 2 and want to use this indicator for that indicator, it is recommended to set your volatility type to Relative Standard Deviation.
Users can also modify the location of the screener to be on the top left, top right, bottom left, or bottom right. You also can disable sections of the screener and show a smaller list if you want to.
The Contraction & Expansion Screener shows you the following information:
Confirmation of whether or not there is a contraction or expansion
Percentage Rank of the volatility
Volatility MA direction: This screener uses moving averages on the volatility to determine if its increasing over time or decreasing over time.
ATR DeltaThe ATR Delta indicator is based on the concept of Average True Range (ATR), which reflects the average price range over a specified period. By calculating the difference between current and previous ATR values, the ATR Delta provides valuable insights into volatility shifts in the market. This information can help traders identify periods of heightened or diminished price movement, enabling them to adjust their strategies accordingly.
The ATR Delta indicator consists of two main calculations:
-- ATR Calculation : The Average True Range (ATR) is calculated using the specified length parameter. It measures the average price range (including gaps) during that period. A larger ATR value indicates higher volatility, while a smaller value indicates lower volatility.
-- ATR Delta Calculation : The ATR Delta is calculated by subtracting the ATR value of the previous bar from the current ATR value. This calculation captures the change in volatility between the two periods, providing a measure of how volatility has evolved.
Positive ATR Delta values indicate an increase in volatility compared to the previous period. It suggests that price movements have expanded, potentially indicating a more active market. On the other hand, negative ATR Delta values indicate a decrease in volatility compared to the previous period. It suggests that price movements have contracted, potentially signaling a calmer or range-bound market.
The ATR Delta indicator uses coloration to visually represent the relationship between the ATR Delta, zero, and a signal line:
-- Green color is assigned when the ATR Delta is positive, above the signal line, and increasing. This coloration suggests a scenario of higher volatility, as the market is experiencing upward momentum in price swings.
-- Red color is assigned when the ATR Delta is negative, below the signal line, and decreasing. This coloration suggests a scenario of lower volatility, as the market is experiencing downward momentum in price swings.
-- Gray color is assigned for other cases when the ATR Delta and signal line relationship does not meet the above conditions.
These colors are reflected in the columns of the ATR Delta as well as the bar coloration.
The ATR Delta indicator includes a signal line, which acts as a reference for interpreting the ATR Delta values. The signal line is calculated as a moving average (EMA) of the ATR Delta over a specified length. It helps smooth out the ATR Delta fluctuations, providing a clearer indication of the underlying trend in volatility changes. When the ATR Delta crosses above the signal line, it may suggest a potential increase in volatility, indicating a market that is becoming more active. Conversely, when the ATR Delta crosses below the signal line, it may suggest a potential decrease in volatility, indicating a market that is becoming less active.
The coloration of the signal line in the ATR Delta indicator helps to differentiate between positive and negative values and provides further insight into market sentiment. When the signal line is positive, indicating increasing volatility, it is colored lime. This color choice reinforces the bullish sentiment and signifies potential opportunities for trend continuation or breakouts. On the other hand, when the signal line is negative, indicating decreasing volatility, it is colored fuchsia. This color choice highlights the bearish sentiment and suggests potential range-bound or consolidation periods. These colors are reflected in the background of the indicator.
The ATR Delta indicator offers several potential applications for traders:
-- Volatility Analysis : The ATR Delta is invaluable for understanding and analyzing volatility dynamics in the market. Traders can observe the changes in ATR Delta values and use them to assess the current level of price movement. This information can help determine the appropriate strategies and risk management approaches.
-- Breakout Strategies : Traders often use the ATR Delta to identify periods of increased volatility, which frequently accompany breakouts. By monitoring the ATR Delta, traders can anticipate potential price breakouts and adjust their entry and exit levels accordingly.
-- Trend Confirmation : Combining the ATR Delta with trend-following indicators allows traders to validate the strength of a trend. Higher ATR Delta values during an uptrend may indicate stronger momentum and a higher likelihood of continuation. Conversely, lower ATR Delta values during a downtrend may suggest a potential consolidation phase or trend reversal.
Limitations :
-- Lagging Indicator : The ATR Delta indicator is based on historical data and calculates the difference between current and previous ATR values. As a result, it may lag behind real-time market conditions. Traders should be aware of this delay and consider it when making trading decisions. It is advisable to combine the ATR Delta with other indicators or price action analysis for a more comprehensive assessment of market conditions.
-- Parameter Sensitivity : The ATR Delta indicator's effectiveness can be influenced by the selection of its parameters, such as the length of the ATR and signal line. Different market conditions may require adjustments to these parameters to better capture volatility changes. Traders should carefully test and optimize the indicator's parameters to align with the characteristics of the specific market or asset they are trading.
-- Market Regime Changes : The ATR Delta indicator assumes that volatility changes occur gradually. However, in rapidly changing market regimes or during news events, volatility can spike or drop abruptly, potentially rendering the indicator less effective. Traders should exercise caution and consider using additional tools or techniques to identify and adapt to such market conditions.
The ATR Delta indicator is a valuable tool for traders seeking to analyze and monitor volatility dynamics in the market. By calculating the difference between current and previous ATR values, it provides insights into changes in price movement and helps identify periods of increased or decreased volatility. Traders can leverage the ATR Delta to fine-tune their strategies, validate trend strength, and identify potential breakout opportunities. However, it is essential to recognize the limitations of the indicator, including its lagging nature and sensitivity to parameter selection. By combining the ATR Delta with other technical analysis tools and applying sound risk management practices, traders can enhance their decision-making process and potentially improve their trading outcomes.
VolbandsThe Volbands indicator dynamically plots upper and lower volatility bands based on implied daily moves derived from volatility indices. This tool provides a visual forecast of the next trading day's price range, helping traders anticipate potential price movement boundaries.
Key Features:
1. Auto-Detect Volatility Index: Volbands automatically detects the appropriate volatility index based on the current symbol. For example, it uses the VIX for S&P 500, VXN for Nasdaq 100, and custom indexes like VXAPL for Apple. Users can also manually select a specific volatility index if preferred.
2. Projected Bands:
- The indicator plots the projected upper and lower bands for the next trading day using the implied move from the volatility index.
- Displays today’s projected bands as a reference and overlays next day’s bands with a slight offset, visually indicating the anticipated range.
3. Dynamic Updates: The indicator updates automatically as new bars are added, ensuring that users have up-to-date projections based on the latest volatility data.
4. Highlighting Extreme Price Action: Candles that close outside of the projected bands are colored in yellow, highlighting moments of higher-than-expected volatility.
5. Informative Table: A customizable table displays relevant information, including:
- The selected or auto-detected volatility index
- Implied daily move percentage
- Projected upper and lower levels
Potential Applications:
- Risk Management: The Volbands indicator can help traders set more informed stop-loss and take-profit levels based on volatility-driven price projections.
- Identifying Overbought/Oversold Conditions: Price movement outside the projected bands may indicate overbought or oversold conditions, potentially signaling trade opportunities.
-Enhancing Entry and Exit Points: The projected bands act as soft support and resistance levels, assisting traders in timing entries and exits in anticipation of volatility-driven price reactions.
Future Enhancements:
Potential improvements to expand functionality could include:
- Additional Volatility Indices: Expanding coverage to include more assets and volatility indices.
- Alerts: Setting alerts for when prices breach the projected bands, enabling traders to react quickly to unexpected price movements.
- Customization of Bands: Adding options for users to adjust the implied move percentage, creating customized bands that reflect individual trading strategies.
This indicator combines implied volatility with price action, offering valuable insights to traders on expected price ranges and volatility.
DTR & ATR
Description
This ATR and DTR label is update of Existing Label provided by © ssksubam
Please See Notes on original Script Here :
Original Code is not mine but I have done few code changes which I believe will help everyone who are looking to add more labels together and save space on the chart
ATR & DTR Script is very helpful for Day Traders as I will explain in detail bellow
Following are changes I have incorporated
Previous Label took more space on the charts with Header and Footer.
I removed the Header and moved both DTR vs ATR descriptions on the same line, saving space on the chart.
I updated the code to remove => signs, which are self-explanatory as I will explain below.
I made the label in 1 single compact line for maximum space efficiency and aesthetics.
These changes improve the content's clarity and conciseness while optimizing space on the charts. If you have any further requests or need additional assistance, feel free to let me know!
What Does DTR Signify?
Stock ATR stands for Average True Range, which is a technical indicator used in trading and investment analysis. The Average True Range measures the volatility of a stock over a given period of time. It provides insights into the price movement and potential price ranges of the stock.
The ATR is calculated as the average of the true ranges over a specific number of periods. The true range is the greatest of the following three values:
The difference between the current high and the current low.
The absolute value of the difference between the current high and the previous close.
The absolute value of the difference between the current low and the previous close.
Traders and investors use ATR to assess the potential risk and reward of a stock. A higher ATR value indicates higher volatility and larger price swings, while a lower ATR value suggests lower volatility and smaller price movements. By understanding the ATR, traders can set appropriate stop-loss levels and make informed decisions about position sizing and risk management.
It's important to note that the ATR is not a directional indicator like moving averages or oscillators. Instead, it provides a measure of volatility, helping traders adapt their strategies to suit the current market conditions.
What Does ATR Signify?
The Average True Range (ATR) signifies the level of volatility or price variability in a particular financial asset, such as a stock, currency pair, or commodity, over a specific period of time. It provides valuable information to traders and investors regarding the potential risk and reward associated with the asset.
Here are the key significances of ATR:
Volatility Measurement: ATR measures the average price range between high and low prices over a specified timeframe. Higher ATR values indicate greater volatility, while lower values suggest lower volatility. Traders use this information to gauge the potential price movements and adjust their strategies accordingly.
Risk Assessment: A higher ATR value implies larger price swings, indicating increased market uncertainty and risk. Traders can use ATR to set appropriate stop-loss levels and manage risk by adjusting position sizes based on the current volatility.
Trend Strength: ATR can also be used to assess the strength of a trend. In an uptrend or downtrend, ATR tends to increase, indicating a more powerful price movement. Conversely, a declining ATR might signify a weakening trend or a consolidation period.
Range-Bound Market Identification: In a range-bound or sideways market, the ATR value tends to be relatively low, reflecting the lack of significant price movements. This information can be helpful for range-trading strategies.
Volatility Breakouts: Traders often use ATR to identify potential breakouts from consolidation patterns. When the ATR value expands significantly, it may indicate the beginning of a new trend or a breakout move.
Comparison between Assets: ATR allows traders to compare the volatility of different
How to use DTR & ATR for Trading
Using Average True Range (ATR) and Daily Trading Range (DTR) can be beneficial for day trading to assess potential price movements, manage risk, and identify trading opportunities. Here's how you can use both indicators effectively:
Calculate ATR and DTR: First, calculate the ATR and DTR values for the asset you are interested in trading. ATR is the average of true ranges over a specified period (e.g., 14 days), while DTR is the difference between the high and low prices of a single trading day.
Assess Volatility: Compare the ATR and DTR values to understand the current volatility of the asset. Higher values indicate increased volatility, while lower values suggest reduced volatility.
Setting Stop-Loss: Use ATR to set appropriate stop-loss levels. For example, you might decide to set your stop-loss a certain number of ATR points away from your entry point. This approach allows you to factor in market volatility when determining your risk tolerance.
Identify Trading Range: Analyze DTR to determine the typical daily price range of the asset. This information can help you identify potential support and resistance levels, which are essential for day trading strategies such as breakout or range trading.
Breakout Strategies: ATR can assist in identifying potential breakout opportunities. When ATR values increase significantly, it suggests an expansion in volatility, which may indicate an upcoming breakout from a trading range. Look for breakouts above resistance or below support levels with higher than usual ATR values.
Scalping Strategies: For scalping strategies, where traders aim to profit from small price movements within a single trading session, knowing the typical DTR can help set reasonable profit targets and stop-loss levels.
Confirming Trend Strength: In day trading, you may encounter short-term trends. Use ATR to assess the strength of these trends. If the ATR is rising, it suggests a strong trend, while a declining ATR may indicate a weakening trend or potential reversal.
Risk Management: Both ATR and DTR can aid in risk management. Determine your position size based on the current ATR value to align it with your risk tolerance. Additionally, understanding the DTR can help you avoid overtrading during periods of low volatility.
Combine with Other Indicators: ATR and DTR work well when used in conjunction with other technical indicators like moving averages, Bollinger Bands, or RSI. Combining multiple indicators can provide a mor
GKD-V Cercos Chaos vs Movement [Loxx]Giga Kaleidoscope GKD-V Cercos Chaos vs Movement is a Volatility/Volume module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-V Cercos Chaos vs Movement
The following aims to provide a detailed explanation of Cercos Chaos vs Movement that helps traders determine market volatility by comparing two different measures: Buffer Move and Buffer Chaos. This indicator is non-directional and should be paired with a directional indicator to provide trading signals.
The first step in the process is defining a custom function that implements a variant of the sigmoid function. This function has a parameter that allows the output to be limited to the range of if desired. The sigmoid function will later be used to normalize the Buffer Chaos value.
Next, several input parameters are introduced, which can be adjusted by the user. These parameters include the period, chaos strength, chaos width, and movement strength. These values are essential to customizing the behavior of the indicator and adapting it to different market conditions and trading styles.
The wicks of the candles in the given time series are then calculated by subtracting the absolute difference between the open and close prices from the difference between the high and low prices. This step is crucial in determining the level of volatility in the market.
Subsequently, the highest high and lowest low over the defined period are identified by examining the maximum and minimum values of the open and close prices. This information is essential for calculating the total movement in the market over the period being analyzed.
Once the highest high and lowest low are found, the Buffer Move and Buffer Chaos values are calculated. The Buffer Move is the sum of the differences between the high and low prices for each candle in the period. This measure helps to identify the overall price movement in the market during the period.
On the other hand, the Buffer Chaos represents the sum of the wicks' lengths for each candle in the period. This measure is used to identify the level of uncertainty and disorder in the market during the period.
In the next step, the total movement in the market is calculated by subtracting the lowest low from the highest high. This value is then used to normalize the Buffer Move and Buffer Chaos values, ensuring they are on a comparable scale.
A comparison is made between the normalized Buffer Move and Buffer Chaos values. If the Buffer Move value is greater than the Buffer Chaos value, it indicates that there is enough volatility in the market to trade long or short. In such a case, the indicator suggests that the market conditions are favorable for trading. However, as this indicator is non-directional, a directional indicator should be used in conjunction with it to provide trading signals.
In conclusion, this custom trading indicator provides valuable insights into market volatility by comparing the Buffer Move and Buffer Chaos values. By offering a non-directional perspective, traders can use this indicator to gauge the potential for profitable trades and make informed decisions by pairing it with a directional indicator.
Additional Features
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
It's important to note that, like any other technical analysis tool, Heiken Ashi "better" candles are not foolproof and should be used in conjunction with other indicators and analysis techniques to make well-informed trading decisions.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Cercos Chaos vs Movement as shown on the chart above
Confirmation 1: Fisher Transform
Confirmation 2: Williams Percent Range
Continuation: Cercos Chaos vs Movement
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Chained: GKD-B Baseline
Solo: NA, no inputs
Baseline + Volatility/Volume: GKD-B Baseline
Outputs
Chained: GKD-C indicators Confirmation 1 or Solo Confirmation Complex
Solo: GKD-BT Backtest
Baseline + Volatility/Volume: GKD-BT Backtest
Additional features will be added in future releases.
Black-Scholes Model and Greeks for European OptionsThe Black-Scholes model is a mathematical model used for pricing options. From this model you can derive the theoretical fair value of a European option (an option where you have to wait until expiry to exercise). Additionally, you can derive various risk parameters called Greeks. This indicator includes three types of data: Theoretical Option Price (blue), the Greeks (green), and implied volatility (red); their values are presented in that order.
1) Theoretical Option Price:
This first value gives only the theoretical fair value of an option with a given strike based on the Black-Scholes framework. Remember this is a model and does not reflect actual option prices, just the theoretical price based on the Black-Scholes model and its parameters and assumptions.
2)Greeks (all of the Greeks included in this indicator are listed below):
a)Delta is the rate of change of the theoretical option price with respect to the change in the underlying's price. This can also be used to approximate the probability of your option expiring in the money. For example, if you have an option with a delta of 0.62, then it has about a 62% chance of expiring in-the-money. This number runs from 0 to 1 for Calls, and 0 to -1 for Puts.
b)Gamma is the rate of change of delta with respect to the change in the underlying's price.
c)Theta, aka "time decay", is the rate of change in the theoretical option price with respect to the change in time. Theta tells you how much an option will lose its value day by day.
d)Vega is the rate of change in the theoretical option price with respect to change in implied volatility.
e)Rho is the rate of change in the theoretical option price with respect to change in the risk-free rate. Rho is rarely used because it is the parameter that options are least effected by, it is more useful for longer term options, like LEAPs.
f)Vanna is the sensitivity of delta to changes in implied volatility. Vanna is useful for checking the effectiveness of delta-hedged and vega-hedged portfolios.
g)Charm, aka "delta decay", is the instantaneous rate of change of delta over time. Charm is useful for monitoring delta-hedged positions.
h)Vomma measures the sensitivity of vega to changes in implied volatility.
i)Veta measures the rate of change in vega with respect to time.
j)Vera measures the rate of change of rho with respect to implied volatility.
k)Speed measures the rate of change in gamma with respect to changes in the underlying's price. Speed can be used when evaluating delta-hedged and gamma hedged portfolios.
l)Zomma measures the rate of change in gamma with respect to changes in implied volatility. Zomma can be used to evaluate the effectiveness of a gamma-hedged portfolio.
m)Color, aka "gamma decay", measures the rate of change of gamma over time. This can also be used to evaluate the effectiveness of a gamma-hedged portfolio.
n)Ultima measures the rate of change in vomma with respect to implied volatility.
o)Probability of Touch, is not a Greek, but a metric that I included, which tells you the probability of price touching your strike price before expiry.
3) Implied Volatility:
This is the market's forecast of future volatility. Implied volatility is directionless, it cannot be used to forecast future direction. All it tells you is the forecast for future volatility.
How to use this indicator:
1st. Input the strike price of your option. If you input a strike that is more than 3 standard deviations away from the current price, the model will return a value of n/a.
2nd. Input the current risk-free rate.(Including this is optional, because the risk-free rate is so small, you can just leave this number at zero.)
3rd. Input the time until expiry. You can enter this in terms of days, hours, and minutes.
4th.Input the chart time frame you are using in terms of minutes. For example if you're using the 1min time frame input 1, 4 hr time frame input 480, daily time frame input 1440, etc.
5th. Pick what type of option you want data for, Long Call or Long Put.
6th. Finally, pick which Greek you want displayed from the drop-down list.
*Remember the Option price presented, and the Greeks presented, are theoretical in nature, and not based upon actual option prices. Also, remember the Black-Scholes model is just a model based upon various parameters, it is not an actual representation of reality, only a theoretical one.
GA - Value at RiskGA Value at Risk is a multifunctional tool. Its main purpose is to plot on the chart the Value at Risk . But it shows also integrated features related to the Volatility.
Value at Risk is a measure of the risk of loss for investments, given normal market conditions, in a period.
It measures and quantifies the level of financial risk. In this case, the risk is within position over a specific time frame.
Defining p as VaR, the probability of a loss greater than VaR is p, at most. Instead, the probability of loss that is less than VaR is 1-p, at least.
The VaR Breach occurs when a loss exceeds the VaR threshold .
For this case, VaR calculation uses the volatility estimation in a time interval. It defines the Probability Confidence according to the Normal Distribution. VaR is a percentile of the Normal Distribution. This is a multiplier of the Standard Deviation that define a Volatility Range.
The Normal Distribution Area around +- the Standard Deviation gives 68% of Confidence. 2 times the Standard Deviation returns a 95% of probability area. 3 time the Standard Deviation the Area returns 99.7% of Confidence.
Knowing VaR modeling, it is possible to determine the amount of a potential loss . Then, it is possible to know if there is enough capital to cover losses. In the same way, higher-than-acceptable risks forces reducing exposure in a financial instrument.
One of its practical use is to estimate the risk of an investment that is already at portfolio. Indeed, this is the purpose of the Value at Risk calculated in this script.
At the VaR Breach that investment has reached its worst scenario. Then, it can be the case to manage that investment into the balanced portfolio.
The Value at Risk does not tell when to enter the market.
Moving Averages
GA Value at Risk bases its calculations on a set of Moving Averages. Every feature of the script uses one of these Moving Averages for its algorithm.
Moving Averages from MA0 to MA8, are the core of each feature of the script.
By default, from MA0 to MA8, Moving Averages use the Fibonacci Series to define their lengths. This happens because of the power of the Golden Ratio in the market behavior.
Instead, the first moving average is an extra resource. Its purpose is to plot a Signal Line on the chart.
The script does not consider plotting every Moving Average on the chart. But it lets you enable the plotting of 7 Moving Averages (from MA0 to MA5 + Signal Line).
It is possible to select the Moving Average Formula to use in the script. This is a setting that affects every Moving Average. Then, it changes also the result of every feature of the script.
The selection is between:
Exponential Moving Average.
Simple Moving Average.
Weighted moving Average.
Simple Moving Averages and Pointers - Full Visibility
Moving Averages and Partial Visibility
The plotting of each Moving Average can be total or partial.
By default, the plotting of Moving Averages and Signal Line is partial.
When the price approaches a Moving Average a little part of the curve becomes visible. This highlights supports or resistances.
Besides, this tracking remains on the chart. Then it shows supports and resistances that the price reached during its progression.
The Partial Visibility Algorithm is a great advantage, ruling how to plot curves. It uses a parameter to set how much of the curves is to plot.
Exponential Moving Averages and Pointers - Partial Visibility
Exponential Moving Averages and Pointers - Full Visibility
Moving Averages and Pointers
As it is clear, it is not necessary to plot entire curves of Moving Averages on the chart. But it becomes relevant to plot Pointers to Moving Averages.
Indeed, the script plots horizontal segments that point to the latest Average Prices.
Every segment has a Label that shows Average Price, Length, and its related Moving Average (from MA0 to MA8). Besides, it is possible to extend the segment to right.
These pointers are a very useful automatization. They point to the Moving Averages. In this way, they show Dynamic Supports and Resistances as horizontal segments.
They are adaptive. Used together with the Volume Profile their progression approaches Edges of High Nodes.
This adaptive behavior makes easy to see when the price reaches Volume High Nodes and slows down.
Moving Average Pointers use the Partial Visibility Algorithm. In this case, the algorithm shows pointers with higher frequency than curves.
Moving Averages Pointers have:
Horizontal Segment as a Pointer with Arrow.
Label with details.
Circle to the current Average Price.
Weighted Moving Averages and Pointers - Full Visibility
Volatility Channels
Having Moving Averages, from MA0 to MA8, it is possible to plot 9 Volatility Channels.
Each Volatility Channel uses one of the Moving Averages, from MA0 to MA8.
Indeed, each Volatility Channel has the same designation of the Moving Average used.
The Standard Deviation defines the Volatility Range. It uses the length of the Moving Average related to the Volatility Channel.
The Volatility Range is unique for each Volatility Channel. In the same way, each Volatility Channel is unique because of its relation to only one Moving Average.
By default, each volatility channel has the 2 value as Standard Deviation Multiplier. This gives 95% of Confidence that the price will stay into the Volatility Range.
Using the Simple Moving Average, each Volatility Channel becomes a Bollinger Bands envelop.
Volatility Channels work very well even using Exponential or Weighted Moving Averages.
MA0 - Volatility Channel
Volatility Channels - From MA0 to MA8
Value at Risk (VaR)
GA Value at Risk plots VaR according to the volatility. The VaR plotting follows the Trend Momentum or Buying-Selling Waves.
By default, VaR follows the Trend Momentum by 2 times the Standard Deviation of MA0. Where MA0 is the first Moving Average and Volatility Channel of the set.
Besides, by default, the calculation of the Value at Risk is adaptive. It does not follow the Volatility Channel Bands. But it changes according to the fast reaction of the price into the Volatility Range.
By default, VaR follows the main momentum even if the price is moving in opposition to it. This occurs as long as the Trend Momentum persists.
In the settings box, It is possible to select the following of the latest Buying Wave or Selling Wave.
In this case, VaR changes according to the change of Buying Wave or Selling Wave. This means that, on these conditions, VaR follows main swings. Then it follows the weakening and the strengthening of the trend momentum as long as it persists.
The plotting of the Value at Risk can show these features:
Red cycle to show the Value at Risk at the current price.
Look Back Red Line that shows the progression of the Value at Risk.
Label with details.
MA0 - Value at Risk - Not Adaptive
MA0 - Value at Risk - Adaptive
It is possible to use a different Moving Average and Volatility Channel from the set. This affects the calculation and the plotting of the Value at Risk. In this way, the algorithm return the Value at Risk for the short, middle, or long-term.
Then, you can get the Value at Risk for that Financial Instrument, calculated for ~1 year or more so as for 1 month.
The Value at Risk does not tell you when to enter the market. Besides, it does not show you that the trend is changing.
MA3 - Value at Risk - Adaptive
Value at Profit (VaP)
The Value at Profit has a descriptive purpose. It points the Volatility Band that is opposite to the Value at Risk.
I chose Value at Profit as a designation for this feature. It does not tell you where to exit the market.
But is shows what the price progression is pointing on. This happens following the switching between Volatility Ranges.
The VaP follows the Volatility Band where the price tends to converge.
An outperforming or underperforming price is running faster than the average trend. Then when the price runs enough to converge to the Volatility Band, it is over extended or under extended.
At these conditions, the increased buying or selling pressure affects the price behavior. This slows down the price progression.
The Algorithm behind the Value at Profit is adaptive. Then the pointer jumps up and down the Volatility Bands of the 9 Volatility Channels. This occurs according to the price progression, following the switching between Volatility Ranges.
So, the VaP points a Volatility Band as long as the price can have chances to converges on it. Instead, when the price has chances to exceed the Volatility Band, the VaP points to the next one.
The plotting of the Value at Profit occurs enabling its Label with details.
Value at Profit - MA0 Volatility Channel Upper Band
Value at Profit - MA6 Volatility Channel Upper Band
Price Extension
When the price runs far away from the average trend price, GA Value at Risk can plot the price extension.
It shows the distance in percentage of the price from a Moving Average of the set. This tends to highlight conditions where the price is over or under extended.
An overbought or oversold condition precedes the shortening of the Trust. It is a cause of the hesitation of the price to continue its progression. This includes also Climactic Points and Signs of Dominance.
The Price Extension plotting uses a variation of the Partial Visibility Algorithm. It plots the Price Extension Arrow only when there are specific volatility conditions.
When the Partial Visibility is set to 0, the Price Extension Arrow is always visible on the chart.
The plotting of the Price Extension includes a Label with details.
Over Extension - The Price is Outperforming MA0
Under Extension - The Price is Underperforming MA0
Price Extension Coloring for Bars and Line Chart
GA Value at Risk lets you enable the coloring of vertical charts. Green and Red colors mark the over and under extended price on bars, candle sticks, and also on the Line Chart.
The Price Extension Algorithm colors Bars and Line Chart by a momentum function.
Indeed, the coloring happens following Relative Strength Index or Bollinger Bands %B.
These 2 Momentum functions are different. Indeed, they color the chart according to the purpose of their curves.
Coloring the Line Chart, it is necessary to put on front the script visibility.
Overbought and Oversold Conditions on Line Chart by Bollinger Bands %B
Overbought and Oversold Conditions on Candlesticks Chart by Relative Strength Index
Note: I restrict access to the tool. Use the links in my signature field to gain access to the script. Feel free to send me a PM for any question.
Thank you
Girolamo Aloe
Founder of Profiting Me Finance Analytics
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Disclaimer
Nobody in Girolamo Aloe websites and trading view profile is a Financial Advisor. Nothing therein is intended to be constructed as Financial Advice. The content on his websites is for information and educational purposes only.
Trading carries high risk. You should not invest money that you cannot afford to lose. Past performance is not an indication of future results.
VIX AnalyticsThis script is designed to serve traders, analysts, and investors who want a real-time, comprehensive view of market volatility, risk sentiment, and implied movements. It combines multiple institutional-grade volatility indices into one clear dashboard and interprets them with actionable insights — directly on your chart.
🔍 Features Included
🟦VIX (CBOE Volatility Index)
Measures market expectation of 30-day S&P 500 volatility.
Color-coded interpretation ranges:
Under 13: Extreme Complacency
15–20: Stable Market
20–30: Moderate Risk
30–40: High Volatility
Over 40: Panic
🟪 VVIX (Volatility of Volatility Index)
Tracks the volatility of VIX itself.
Interpreted as a risk gauge of how aggressively traders are hedging volatility exposure.
Under 80: Market Complacency
80–100: Normal Environment
100–120: Caution — Rising Volatility of Volatility
Over 120: High Stress — Elevated Hedging Activity
🟨 SKEW Index
Measures the perceived tail risk of the S&P 500 — i.e., the probability of a black swan event.
Below 110: Potential Complacency
120–140: Moderate Tail Risk
Above 140: High Tail Risk
🧮 VIX/VVIX Ratio
Gauges relative fear levels between expected volatility and the volatility of volatility.
Under 0.5: Low Ratio — VVIX Overextended
Over 0.9: High Ratio — VIX Leading
📈 VIX Percentile (1-Year Range)
Shows where the current VIX sits relative to its 1-year high/low.
Under 20%: Volatility is Cheap
Over 70%: Fear is Elevated — Reversal Possible
📉 SPX Implied Point Moves
Projects expected moves in SPX using VIX-derived volatility:
Daily
Weekly
Monthly
Helps size positions or define expected price ranges based on volatility regime.
📊 ATR Values (5, 13, 21 periods)
Traditional volatility using historical prices.
Provided alongside implied data for comparison.
🧠 Unique Logic & Interpretation Layer
This script doesn’t just show raw data — it interprets it. It reads the relationship between VIX, VVIX, and SKEW to highlight:
When market volatility may be underpriced
When hidden tail risks are forming
When to be cautious of volatility expansions
How current implied movement compares to past realized volatility
✅ Use Cases
Day traders: Know when volatility is low or expanding before scalping or swinging.
Options traders: Identify whether implied volatility is cheap or expensive.
Portfolio managers: Gauge when hedging is in demand and adjust exposure.
Risk managers: Crosscheck if current volatility aligns with macro risk events.
⚙️ Settings
Customizable table placement: Move the dashboard to any corner of your chart.
No repainting or lag: Data updates in real-time using official CBOE and SPX feeds.
ADR (Log Scale) with MTF LabelsHere's a detailed presentation of the Average Daily Range (ADR) indicator, with a focus on its advantages compared to the classic ADR, its unique features, utility, and interpretation:
Advantages Compared to Classic ADR
1. Logarithmic Scale: Unlike the classic ADR, which uses a linear scale, this version uses a logarithmic scale for calculations. This approach provides a more accurate representation of relative price movements, especially for assets with large price ranges.
2. Multi-Timeframe Analysis: This enhanced ADR indicator allows traders to view daily, weekly, and monthly ADRs simultaneously. This multi-timeframe capability helps traders understand volatility trends over different periods, offering a more comprehensive market analysis.
3. Optional Smoothing: The inclusion of an optional smoothing feature (using Exponential Moving Average, EMA) helps reduce noise in the data. This makes the indicator more reliable by filtering out short-term fluctuations and highlighting the underlying volatility trend.
4. Information Display Labels: The indicator includes labels that display precise ADR values for each timeframe directly on the chart. This feature provides immediate, clear insights without requiring additional calculations or references.
Utility of the Indicator
1. Volatility Analysis: The ADR indicator is essential for assessing market volatility. By showing the average daily price range, it helps traders gauge how much an asset typically moves within a day, week, or month.
2. Risk Management: ADR levels can be used to set stop-loss points, improving risk management strategies. Knowing the average range helps traders avoid setting stops too close to the current price, which might otherwise be triggered by normal market fluctuations.
3. Setting Realistic Targets: By understanding the average daily range, traders can set more realistic profit targets. This helps in avoiding over-ambitious goals that are unlikely to be reached within the typical market movement.
4. Identifying Entry and Exit Points: The ADR can signal potential entry and exit points. For example, if the price approaches the upper or lower ADR boundary, it might indicate an overbought or oversold condition, respectively.
Interpretation and Examples
1. Increasing Volatility: If the ADR is increasing, it indicates rising market volatility. Traders might adjust their strategies accordingly, such as widening their stop-losses to accommodate larger price swings.
2. Range Breakout: If the price significantly exceeds the daily ADR, it may signal a strong trend or exceptional market movement. Traders can use this information to stay in the trade longer or to anticipate a potential reversal.
3. Mean Reversion: Prices often revert to the ADR mean. A trader might consider mean reversion trades when the price approaches the extremes of the ADR range, expecting it to move back towards the average.
4. Multi-Timeframe Comparison: If the daily ADR is higher than the weekly ADR, it may indicate unusually high short-term volatility. This can be a signal for traders to be cautious or to capitalize on the increased movement.
While the ADR indicator provides valuable insights into market volatility and can significantly enhance trading strategies, it is essential to remember that no indicator is foolproof. Market conditions can change rapidly, and past performance is not always indicative of future results. Traders should use the ADR indicator in conjunction with other tools and follow sound risk management practices to protect their capital.
Session-Based Sentiment Oscillator [TradeDots]Track, analyze, and monitor market sentiment across global trading sessions with this advanced multi-session sentiment analysis tool. This script provides session-specific sentiment readings for Asian (Tokyo), European (London), and US (New York) markets, combining price action, volume analysis, and volatility factors into a comprehensive sentiment oscillator. It is an original indicator designed to help traders understand regional market psychology and capitalize on cross-session sentiment shifts directly on TradingView.
📝 HOW IT WORKS
1. Multi-Component Sentiment Engine
Price Action Momentum : Calculates normalized price movement relative to recent trading ranges, providing directional sentiment readings.
Volume-Weighted Analysis : When volume data is available, incorporates volume flow direction to validate price-based sentiment signals.
Volatility-Adjusted Factors : Accounts for changing market volatility conditions by comparing current ATR against historical averages.
Weighted Combination : Merges all components using optimized weightings (Price: 1.0, Volume: 0.3, Volatility: 0.2) for balanced sentiment readings.
2. Session-Segregated Tracking
Automatic Session Detection : Precisely identifies active trading sessions based on user-configured time parameters.
Independent Calculations : Maintains separate sentiment accumulation for each major session, updated only during respective active hours.
Historical Preservation : Stores session-specific sentiment values even when sessions are closed, enabling cross-session comparison.
Real-Time Updates : Continuously processes sentiment during active sessions while preserving inactive session data.
3. Cross-Session Transition Analysis
Sentiment Differential Detection : Monitors sentiment changes when transitioning between trading sessions.
Configurable Thresholds : Generates signals only when sentiment shifts exceed user-defined minimum thresholds.
Directional Signals : Provides distinct bullish and bearish transition alerts with visual markers.
Smart Filtering : Applies smoothing algorithms to reduce false signals from minor sentiment variations.
⚙️ KEY FEATURES
1. Session-Specific Dashboard
Real-Time Status Display : Shows current session activity (ACTIVE/CLOSED) for all three major sessions.
Sentiment Percentages : Displays precise sentiment readings as percentages for easy interpretation.
Strength Classification : Automatically categorizes sentiment as HIGH (>50%), MEDIUM (20-50%), or LOW (<20%).
Customizable Positioning : Place dashboard in any corner with adjustable size options.
2. Advanced Signal Generation
Transition Alerts : Triangle markers indicate significant sentiment shifts between sessions.
Extreme Conditions : Diamond markers highlight overbought/oversold threshold breaches.
Configurable Sensitivity : Adjust signal thresholds from 0.05 to 0.50 based on trading style.
Alert Integration : Built-in TradingView alert conditions for automated notifications.
3. Forex Currency Strength Analysis
Base/Quote Decomposition : For forex pairs, separates sentiment into individual currency strength components.
Major Currency Support : Analyzes USD, EUR, GBP, JPY, CHF, CAD, AUD, NZD strength relationships.
Relative Strength Display : Shows which currency is driving pair movement during active sessions.
4. Visual Enhancement System
Session Background Colors : Distinct background shading for each active trading session.
Overbought/Oversold Zones : Configurable extreme sentiment level visualization with colored zones.
Multi-Timeframe Compatibility : Works across all timeframes while maintaining session accuracy.
Customizable Color Schemes : Full color customization for dashboard, signals, and plot elements.
🚀 HOW TO USE IT
1. Add the Script
Search for "Session-Based Sentiment Oscillator " in the Indicators tab or manually add it to your chart. The indicator will appear in a separate pane below your main chart.
2. Configure Session Times
Asian Session : Set Tokyo market hours (default: 00:00-09:00) based on your chart timezone.
European Session : Configure London market hours (default: 07:00-16:00) for European analysis.
US Session : Define New York market hours (default: 13:00-22:00) for American markets.
Timezone Adjustment : Ensure session times match your broker's specifications and account for daylight saving changes.
3. Optimize Analysis Parameters
Sentiment Period : Choose 5-50 bars (default: 14) for sentiment calculation lookback period.
Smoothing Settings : Select 1-10 bars smoothing (default: 3) with SMA, EMA, or RMA options.
Component Selection : Enable/disable volume analysis, price action, and volatility factors based on available data.
Signal Sensitivity : Adjust threshold from 0.05-0.50 (default: 0.15) for transition signal generation.
4. Interpret Readings and Signals
Positive Values : Indicate bullish sentiment for the active session.
Negative Values : Suggest bearish sentiment conditions.
Dashboard Status : Monitor which session is currently active and their respective sentiment strengths.
Transition Signals : Watch for triangle markers indicating significant cross-session sentiment changes.
Extreme Alerts : Note diamond markers when sentiment reaches overbought (>70%) or oversold (<-70%) levels.
5. Set Up Alerts
Configure TradingView alerts for:
- Bullish session transitions
- Bearish session transitions
- Overbought condition alerts
- Oversold condition alerts
❗️LIMITATIONS
1. Data Dependency
Volume Requirements : Volume-based analysis only functions when volume data is provided by your broker. Many forex brokers do not supply reliable volume data.
Price Action Focus : In absence of volume data, sentiment calculations rely primarily on price movement and volatility factors.
2. Session Time Sensitivity
Manual Adjustment Required : Session times must be manually updated for daylight saving time changes.
Broker Variations : Different brokers may have slightly different session definitions requiring time parameter adjustments.
3. Ranging Market Limitations
Trend Bias : Sentiment calculations may be less reliable during extended sideways or low-volatility market conditions.
Lag Consideration : As with all sentiment indicators, readings may lag during rapid market transitions.
4. Regional Market Focus
Major Session Coverage : Designed primarily for major global sessions; may not capture sentiment from smaller regional markets.
Weekend Gaps : Does not account for weekend gap effects on sentiment calculations.
⚠️ RISK DISCLAIMER
Trading and investing carry significant risk and can result in financial loss. The "Session-Based Sentiment Oscillator " is provided for informational and educational purposes only. It does not constitute financial advice.
- Always conduct your own research and analysis
- Use proper risk management and position sizing in all trades
- Past sentiment patterns do not guarantee future market behavior
- Combine this indicator with other technical and fundamental analysis tools
- Consider overall market context and your personal risk tolerance
This script is an original creation by TradeDots, published under the Mozilla Public License 2.0.
Session-based sentiment analysis should be used as part of a comprehensive trading strategy. No single indicator can predict market movements with certainty. Exercise proper risk management and maintain realistic expectations about indicator performance across varying market conditions.
Bollinger Band Width PercentileIntroducing the Bollinger Band Width Percentile
Definitions :
Bollinger Band Width Percentile is derived from the Bollinger Band Width indicator.
It shows the percentage of bars over a specified lookback period that the Bollinger Band Width was less than the current Bollinger Band Width.
Bollinger Band Width is derived from the Bollinger Bands® indicator.
It quantitatively measures the width between the Upper and Lower Bands of the Bollinger Bands.
Bollinger Bands® is a volatility-based indicator.
It consists of three lines which are plotted in relation to a security's price.
The Middle Line is typically a Simple Moving Average.
The Upper and Lower Bands are typically 2 standard deviations above, and below the SMA (Middle Line).
Volatility is a statistical measure of the dispersion of returns for a given security or market index, measured by the standard deviation of logarithmic returns.
The Broad Concept :
Quoting Tradingview specifically for commonly noted limitations of the BBW indicator which I have based this indicator on....
“ Bollinger Bands Width (BBW) outputs a Percentage Difference between the Upper Band and the Lower Band.
This value is used to define the narrowness of the bands.
What needs to be understood however is that a trader cannot simply look at the BBW value and determine if the Band is truly narrow or not.
The significance of an instruments relative narrowness changes depending on the instrument or security in question.
What is considered narrow for one security may not be for another.
What is considered narrow for one security may even change within the scope of the same security depending on the timeframe.
In order to accurately gauge the significance of a narrowing of the bands, a technical analyst will need to research past BBW fluctuations and price performance to increase trading accuracy. ”
Here I present the Bollinger Band Width Percentile as a refinement of the BBW to somewhat overcome the limitations cited above.
Much of the work researching past BBW fluctuations, and making relative comparisons is done naturally by calculating the Bollinger Band Width Percentile.
This calculation also means that it can be read in a similar fashion across assets, greatly simplifying the interpretation of it.
Plotted Components of the Bollinger Band Width Percentile indicator :
Scale High
Mid Line
Scale Low
BBWP plot
Moving Average 1
Moving Average 2
Extreme High Alert
Extreme Low Alert
Bollinger Band Width Percentile Properties:
BBWP Length
The time period to be used in calculating the Moving average which creates the Basis for the BBW component of the BBWP.
Basis Type
The type of moving average to be used as the Basis for the BBW component of the BBWP.
BBWP Lookback
The lookback period to be used in calculating the BBWP itself.
BBWP Plot settings
The BBWP plot settings give a choice between a user defined solid color, and a choice of "Blue Green Red", or "Blue Red" spectrum palettes.
Moving Averages
Has 2 Optional User definable and adjustable moving averages of the BBWP.
Visual Alerts
Optional User adjustable High and low Signal columns.
How to read the BBWP :
A BBWP read of 95 % ... means that the current BBW level is greater than 95% of the lookback period.
A BBWP read of 5 % .... means that the current BBW level is lower than 95% of the lookback period.
Proposed interpretations :
When the BBWP gets above 90 % and particularly when it hits 100% ... this can be a signal that volatility is reaching a maximum and that a macro High or Low is about to be set.
When the BBWP gets below 10 % and particularly when it hits 0% ...... this can be a signal that volatility is reaching a minimum and that there could be a violent range breakout into a trending move.
When the BBWP hits a low level < 5 % and then gets above its moving average ...... this can be an early signal that a consolidation phase is ending and a trending move is beginning.
When the BBWP hits a high level > 95 % and then falls below its moving average ... this can be an early signal that a trending move is ending and a consolidation phase is beginning.
Essential knowledge :
The BBWP was designed with the daily timeframe in mind, but technical analysists may find use for it on other time frames also.
High and Low BBWP readings do not entail any direction bias.
Deeper Concepts :
In finance, “mean reversion” is the assumption that a financial instrument's price will tend to move towards the average price over time.
If we apply that same logic to volatility as represented here by the Bollinger band width percentile, the assumption is that the Bollinger band width percentile will tend to contract from extreme highs, and expand from extreme lows over time corresponding to repeated phases of contraction and expansion of volatility.
It is clear that for most assets there are periods of directional trending behavior followed by periods of “consolidation” ( trading sideways in a range ).
This often ends with a tightening range under reducing volume and volatility ( popularly known as “the squeeze” ).
The squeeze typically ends with a “breakout” from the range characterized by a rapid increase in volume, and volatility when price action again trends directionally, and the cycle repeats.
Typical Use Cases :
The Bollinger Band Width Percentile may be especially useful for Options traders, as it can provide a bias for when Options are relatively expensive, or inexpensive from a Volatility (Vega) perspective.
When the Bollinger Band Width Percentile is relatively high ( 85 percentile or above ) it may be more advantageous to be a net seller of Vega.
When the Bollinger Band Width Percentile is relatively low ( 15 percentile or below ) it may be advantageous to be net long Vega.
Here we examine a number of actionable signals on BTCUSD daily timeframe using the BBWP and a momentum oscillator ( using the TSI here but can equally be used with Bollinger bands, moving averages, or the traders preferred momentum oscillator ).
In this first case we will examine how a spot trader and an options trader could each use a low BBWP read to alert them to a good potential trade setup.
note: using a period of 30 for both the Bollinger bands and the BBWP period ( approximately a month ) and a BBWP lookback of 350 ( approximately a year )
As we see the Bollinger Bands have gradually contracted while price action trended down and the BBWP also fell consistently while below its moving average ( denoting falling volatility ) down to an extremely low level <5% until it broke above its moving average along with a break of range to the upside ( signaling the end of the consolidation at a low level and the beginning of a new trending move to the upside with expanding volatility).
In this next case we will continue to follow the price action presuming that the traders have taken or locked in profit at reasonable take profit levels from the previous trade setup.
Here we see the contraction of the Bollinger bands, and the BBWP alongside price action breaking below the BB Basis giving a warning that the trending move to the upside is likely over.
We then see the BBWP rising and getting above its moving average while price action fails to get above the BB Basis, likewise the TSI fails to get above its signal line and actually crosses below its zeroline.
The trader would normally take this as a signal that the next trending move could be to the downside.
The next trending move turns out to be a dramatic downside move which causes the BBWP to hit 100% signaling that volatility is likely to hit a maximum giving good opportunities for profitable trades to the skilled trader as outlined.
Limitations :
Here we will look at 2 cases where blindly taking BBWP signals could cause the trader to take a failed trade.
In this first example we will look at blindly taking a low volatility options trade
Low Volatility and corresponding low BBWP levels do not automatically mean there has to be expansion immediately, these periods of extreme low volatility can go on for quite some time.
In this second example we will look at blindly taking a high volatility spot short trade
High volatility and corresponding high BBWP levels do not automatically mean there has to be a macro high and contraction of volatility immediately, these periods of extreme high volatility can also go on for quite some time, hence the famous saying "The trend is your friend until the end of the trend" and lesser well known, but equally valid saying "never try to short the top of a parabolic blow off top"
Markets are variable and past performance is no guarantee of future results, this is not financial advice, I am not a financial advisor.
Final thoughts
The BBWP is an improvement over the BBW in my opinion, and is a novel, and useful addition to a Technical Analysts toolkit.
It is not a standalone indicator and is meant to be used in conjunction with other tools for direction bias, and Good Risk Management to base sound trades off.
John Bollinger has suggested using Bolliger bands, and its related indicators with two or three other non-correlated indicators that provide more direct market signals.
He believes it is crucial to use indicators based on different types of data.
Some of his favored technical techniques are moving average divergence/convergence (MACD), on-balance volume and relative strength index (RSI).
Thanks
Massive respect to John Bollinger, long-time technician of the markets, and legendary creator of both the Bollinger Bands® in the 1980´s, and the Bollinger band Width indicator in 2010 which this indicator is based on.
His work continues to inspire, decades after he brought the original Bollinger Bands to the market.
Much respect also to Eric Crown who gave me the fundamental knowledge of Technical Analysis, and Options trading.
Average True Range ShiftThis indicator builds on the idea of the Average True Range (ATR) as a way of measuring volatility. It uses two different ATRs to show a shift in market volatility.
It is mainly composed of two moving averages of ATR. One fast moving, which looks back at the previous 5 periods. One slow moving, which looks back at the previous 21 periods. Both ATRs have been normalized (show percentage instead of an absolute amount). The third component of this indicator is the histogram that is created by subtracting the slow moving average, from the fast moving average.
By having two ATRs of different lengths, traders can see how short term volatility compares to long term volatility, and how it is shifting over time. When the fast-moving crosses above the slow-moving, it will show a positive value on the histogram, meaning that short term volatility is increasing and higher than normal. When it crosses below, it will show a negative value on the histogram, meaning that short term volatility is decreasing, and lower than normal.
There are a variety of ways to utilize this indicator, and it will work in most markets. I find it is best to analyze macro market conditions on daily charts and above, rather than micro intraday moves.
GKD-V Semi-Variance [Loxx]Giga Kaleidoscope Semi-Variance is a Volatility / Volume module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is an NNFX algorithmic trading strategy?
The NNFX algorithm is built on the principles of trend, momentum, and volatility . There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility ; e.g., Average True Range , True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends.
4. Confirmation 2 - a technical indicator used to identify trends.
5. Continuation - a technical indicator used to identify trends.
6. Volatility / Volume - a technical indicator used to identify volatility / volume breakouts/breakdown.
7. Exit - a technical indicator used to determine when a trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility , Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility / Volume , Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility / Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility / Volume . The Volatility / Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Semi-variance as shown on the chart above
Confirmation 1: Halftrend Averages
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility / Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility / Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility / Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility / Volume Agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility / Volume Agrees
█ Semi-Variance
What is Semi-Variance
Semi-variance is a statistical measure that represents the variability of returns in a financial portfolio or investment that fall below a certain threshold or benchmark return. Unlike traditional variance, which measures the dispersion of all returns, semi-variance only focuses on the downside risk or the deviation of returns that are below a specified target return.
Semi-variance is calculated as the average of the squared deviations of returns below the target return. It provides information on the risk of losing money and helps investors assess the stability and reliability of a portfolio or investment. A high semi-variance indicates a higher level of downside risk, while a low semi-variance suggests a lower level of downside risk.
In finance, semi-variance is often used in conjunction with other risk measures, such as standard deviation, beta, and value-at-risk, to give a comprehensive understanding of a portfolio's risk-return profile.
This indicator calculates the difference betwen upward volatility and downward volatility. You can choose between guassian normalized or regular.
Other things to note
The GKD trading system requires that a GKD-V indicator be present in the indicator chain, but the GKD-V indicator doesn't need to be active. You can turn on/off the Volatility Ratio as you wish so you can backtest your trading strategy with the filter on or off.
Additional features will be added in future releases.
GKD-V Loxx Volty [Loxx]Giga Kaleidoscope Loxx Volty is a Volatility/Volume module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is an NNFX algorithmic trading strategy?
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends.
4. Confirmation 2 - a technical indicator used to identify trends.
5. Continuation - a technical indicator used to identify trends.
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
7. Exit - a technical indicator used to determine when a trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Leader Exponential Moving Average
Volatility/Volume: Loxx Volty as shown on the chart above
Confirmation 1: Double Smoothed Stochastic of Momentum
Confirmation 2: Jurik Turning Point Oscillator
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
█ Loxx Volty
What is Loxx Volty
One of the lesser known qualities of Loxx smoothing is that the Loxx smoothing process is adaptive. "Loxx Volty" (a sort of market volatility) is what makes Loxx smoothing adaptive. The Loxx Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
Other things to note
The GKD trading system requires that a GKD-V indicator be present in the indicator chain, but the GKD-V indicator doesn't need to be active. You can turn on/off the Volatility Ratio as you wish so you can backtest your trading strategy with the filter on or off.
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
Hurst Exponent Adaptive Filter (HEAF) [PhenLabs]📊 PhenLabs - Hurst Exponent Adaptive Filter (HEAF)
Version: PineScript™ v6
📌 Description
The Hurst Exponent Adaptive Filter (HEAF) is an advanced Pine Script indicator designed to dynamically adjust moving average calculations based on real time market regimes detected through the Hurst Exponent. The intention behind the creation of this indicator was not a buy/sell indicator but rather a tool to help sharpen traders ability to distinguish regimes in the market mathematically rather than guessing. By analyzing price persistence, it identifies whether the market is trending, mean-reverting, or exhibiting random walk behavior, automatically adapting the MA length to provide more responsive alerts in volatile conditions and smoother outputs in stable ones. This helps traders avoid false signals in choppy markets and capitalize on strong trends, making it ideal for adaptive trading strategies across various timeframes and assets.
Unlike traditional moving averages, HEAF incorporates fractal dimension analysis via the Hurst Exponent to create a self-tuning filter that evolves with market conditions. Traders benefit from visual cues like color coded regimes, adaptive bands for volatility channels, and an information panel that suggests appropriate strategies, enhancing decision making without constant manual adjustments by the user.
🚀 Points of Innovation
Dynamic MA length adjustment using Hurst Exponent for regime-aware filtering, reducing lag in trends and noise in ranges.
Integrated market regime classification (trending, mean-reverting, random) with visual and alert-based notifications.
Customizable color themes and adaptive bands that incorporate ATR for volatility-adjusted channels.
Built-in information panel providing real-time strategy recommendations based on detected regimes.
Power sensitivity parameter to fine-tune adaptation aggressiveness, allowing personalization for different trading styles.
Support for multiple MA types (EMA, SMA, WMA) within an adaptive framework.
🔧 Core Components
Hurst Exponent Calculation: Computes the fractal dimension of price series over a user-defined lookback to detect market persistence or anti-persistence.
Adaptive Length Mechanism: Maps Hurst values to MA lengths between minimum and maximum bounds, using a power function for sensitivity control.
Moving Average Engine: Applies the chosen MA type (EMA, SMA, or WMA) to the adaptive length for the core filter line.
Adaptive Bands: Creates upper and lower channels using ATR multiplied by a band factor, scaled to the current adaptive length.
Regime Detection: Classifies market state with thresholds (e.g., >0.55 for trending) and triggers alerts on regime changes.
Visualization System: Includes gradient fills, regime-colored MA lines, and an info panel for at-a-glance insights.
🔥 Key Features
Regime-Adaptive Filtering: Automatically shortens MA in mean-reverting markets for quick responses and lengthens it in trends for smoother signals, helping traders stay aligned with market dynamics.
Custom Alerts: Notifies on regime shifts and band breakouts, enabling timely strategy adjustments like switching to trend-following in bullish regimes.
Visual Enhancements: Color-coded MA lines, gradient band fills, and an optional info panel that displays market state and trading tips, improving chart readability.
Flexible Settings: Adjustable lookback, min/max lengths, sensitivity power, MA type, and themes to suit various assets and timeframes.
Band Breakout Signals: Highlights potential overbought/oversold conditions via ATR-based channels, useful for entry/exit timing.
🎨 Visualization
Main Adaptive MA Line: Plotted with regime-based colors (e.g., green for trending) to visually indicate market state and filter position relative to price.
Adaptive Bands: Upper and lower lines with gradient fills between them, showing volatility channels that widen in random regimes and tighten in trends.
Price vs. MA Fills: Color-coded areas between price and MA (e.g., bullish green above MA in trending modes) for quick trend strength assessment.
Information Panel: Top-right table displaying current regime (e.g., "Trending Market") and strategy suggestions like "Follow trends" or "Trade ranges."
📖 Usage Guidelines
Core Settings
Hurst Lookback Period
Default: 100
Range: 20-500
Description: Sets the period for Hurst Exponent calculation; longer values provide more stable regime detection but may lag, while shorter ones are more responsive to recent changes.
Minimum MA Length
Default: 10
Range: 5-50
Description: Defines the shortest possible adaptive MA length, ideal for fast responses in mean-reverting conditions.
Maximum MA Length
Default: 200
Range: 50-500
Description: Sets the longest adaptive MA length for smoothing in strong trends; adjust based on asset volatility.
Sensitivity Power
Default: 2.0
Range: 1.0-5.0
Description: Controls how aggressively the length adapts to Hurst changes; higher values make it more sensitive to regime shifts.
MA Type
Default: EMA
Options: EMA, SMA, WMA
Description: Chooses the moving average calculation method; EMA is more responsive, while SMA/WMA offer different weighting.
🖼️ Visual Settings
Show Adaptive Bands
Default: True
Description: Toggles visibility of upper/lower bands for volatility channels.
Band Multiplier
Default: 1.5
Range: 0.5-3.0
Description: Scales band width using ATR; higher values create wider channels for conservative signals.
Show Information Panel
Default: True
Description: Displays regime info and strategy tips in a top-right panel.
MA Line Width
Default: 2
Range: 1-5
Description: Adjusts thickness of the main MA line for better visibility.
Color Theme
Default: Blue
Options: Blue, Classic, Dark Purple, Vibrant
Description: Selects color scheme for MA, bands, and fills to match user preferences.
🚨 Alert Settings
Enable Alerts
Default: True
Description: Activates notifications for regime changes and band breakouts.
✅ Best Use Cases
Trend-Following Strategies: In detected trending regimes, use the adaptive MA as a trailing stop or entry filter for momentum trades.
Range Trading: During mean-reverting periods, monitor band breakouts for buying dips or selling rallies within channels.
Risk Management in Random Markets: Reduce exposure when random walk is detected, using tight stops suggested in the info panel.
Multi-Timeframe Analysis: Apply on higher timeframes for regime confirmation, then drill down to lower ones for entries.
Volatility-Based Entries: Use upper/lower band crossovers as signals in adaptive channels for overbought/oversold trades.
⚠️ Limitations
Lagging in Transitions: Regime detection may delay during rapid market shifts, requiring confirmation from other tools.
Not a Standalone System: Best used in conjunction with other indicators; random regimes can lead to whipsaws if traded aggressively.
Parameter Sensitivity: Optimal settings vary by asset and timeframe, necessitating backtesting.
💡 What Makes This Unique
Hurst-Driven Adaptation: Unlike static MAs, it uses fractal analysis to self-tune, providing regime-specific filtering that's rare in standard indicators.
Integrated Strategy Guidance: The info panel offers actionable tips tied to regimes, bridging analysis and execution.
Multi-Regime Visualization: Combines adaptive bands, colored fills, and alerts in one tool for comprehensive market state awareness.
🔬 How It Works
Hurst Exponent Computation:
Calculates log returns over the lookback period to derive the rescaled range (R/S) ratio.
Normalizes to a 0-1 value, where >0.55 indicates trending, <0.45 mean-reverting, and in-between random.
Length Adaptation:
Maps normalized Hurst to an MA length via a power function, clamping between min and max.
Applies the selected MA type to close prices using this dynamic length.
Visualization and Signals:
Plots the MA with regime colors, adds ATR-based bands, and fills areas for trend strength.
Triggers alerts on regime changes or band crosses, with the info panel suggesting strategies like momentum riding in trends.
💡 Note:
For optimal results, backtest settings on your preferred assets and combine with volume or momentum indicators. Remember, no indicator guarantees profits—use with proper risk management. Access premium features and support at PhenLabs.
ATR BandsThe ATR Bands indicator is a volatility-based tool that plots dynamic support and resistance levels around the price using the Average True Range (ATR). It consists of two bands:
Upper Band: Calculated as current price + ATR, representing an upper volatility threshold.
Lower Band: Calculated as current price - ATR, serving as a lower volatility threshold.
Key Features:
✅ Measures Volatility: Expands and contracts based on market volatility.
✅ Dynamic Support & Resistance: Helps identify potential breakout or reversal zones.
✅ Customizable Smoothing: Supports multiple moving average methods (RMA, SMA, EMA, WMA) for ATR calculation.
How to Use:
Trend Confirmation: If the price consistently touches or exceeds the upper band, it may indicate strong bullish momentum.
Reversal Signals: A price approaching the lower band may suggest a potential reversal or increased selling pressure.
Volatility Assessment: Wide bands indicate high volatility, while narrow bands suggest consolidation.
This indicator is useful for traders looking to incorporate volatility-based strategies into their trading decisions
Trend Analysis with Volatility and MomentumVolatility and Momentum Trend Analyzer
The Volatility and Momentum Trend Analyzer is a multi-faceted TradingView indicator designed to provide a comprehensive analysis of market trends, volatility, and momentum. It incorporates key features to identify trend direction (uptrend, downtrend, or sideways), visualize weekly support and resistance levels, and offer a detailed assessment of market strength and activity. Below is a breakdown of its functionality:
1. Input Parameters
The indicator provides customizable settings for precision and adaptability:
Volatility Lookback Period: Configurable period (default: 14) for calculating Average True Range (ATR), which measures market volatility.
Momentum Lookback Period: Configurable period (default: 14) for calculating the Rate of Change (ROC), which measures the speed and strength of price movements.
Support/Resistance Lookback Period: Configurable period (default: 7 weeks) to determine critical support and resistance levels based on weekly high and low prices.
2. Volatility Analysis (ATR)
The Average True Range (ATR) is calculated to quantify the market's volatility:
What It Does: ATR measures the average range of price movement over the specified lookback period.
Visualization: Plotted as a purple line in a separate panel below the price chart, with values amplified (multiplied by 10) for better visibility.
3. Momentum Analysis (ROC)
The Rate of Change (ROC) evaluates the momentum of price movements:
What It Does: ROC calculates the percentage change in closing prices over the specified lookback period, indicating the strength and direction of market moves.
Visualization: Plotted as a yellow line in a separate panel below the price chart, with values amplified (multiplied by 10) for better visibility.
4. Trend Detection
The indicator identifies the current market trend based on momentum and the position of the price relative to its moving average:
Uptrend: Occurs when momentum is positive, and the closing price is above the simple moving average (SMA) of the specified lookback period.
Downtrend: Occurs when momentum is negative, and the closing price is below the SMA.
Sideways Trend: Occurs when neither of the above conditions is met.
Visualization: The background of the price chart changes color to reflect the detected trend:
Green: Uptrend.
Red: Downtrend.
Gray: Sideways trend.
5. Weekly Support and Resistance
Critical levels are calculated based on weekly high and low prices:
Support: The lowest price observed over the last specified number of weeks.
Resistance: The highest price observed over the last specified number of weeks.
Visualization:
Blue Line: Indicates the support level.
Orange Line: Indicates the resistance level.
Both lines are displayed on the main price chart, dynamically updating as new data becomes available.
6. Alerts
The indicator provides configurable alerts for trend changes, helping traders stay informed without constant monitoring:
Uptrend Alert: Notifies when the market enters an uptrend.
Downtrend Alert: Notifies when the market enters a downtrend.
Sideways Alert: Notifies when the market moves sideways.
7. Key Use Cases
Trend Following: Identify and follow the dominant trend to capitalize on sustained price movements.
Volatility Assessment: Measure market activity to determine potential breakouts or quiet consolidation phases.
Support and Resistance: Highlight key levels where price is likely to react, assisting in decision-making for entries, exits, or stop-loss placement.
Momentum Tracking: Gauge the strength and speed of price moves to validate trends or anticipate reversals.
8. Visualization Summary
Main Chart:
Background color-coded for trend direction (green, red, gray).
Blue and orange lines for weekly support and resistance.
Lower Panels:
Purple line for volatility (ATR).
Yellow line for momentum (ROC).
VIX Bars [CrossTrade]In simple terms, this indicator colors your chart bars based on the VIX levels. We know that high volatility is unstainable and will naturally regress to a calmer market, therefore highlighting the bars where VIX is at extreme highs can sometimes indicate a market turning point. Consider pairing this indicator with my VIX Heatmap indicator for a complete picture of volatility.
Customizable VIX Levels: You can set your own thresholds for when the bars turn green or red. Green bars pop up when the VIX is above your set upper level (default is 30) - kind of like a heads-up that things might get bumpy. Red bars show up when the VIX dips below your lower threshold (default is 15), signaling calmer waters.
Optional Donchian Channel Filter: The Donchian Channel filter looks at the highest highs and lowest lows over your chosen period (default's 52 days) and only colors the bars if they match the filter's criteria. This adds an extra layer of confirmation that the colored bars at at a major high or low.
Visual Simplicity: The indicator keeps things visually straightforward. No cluttered screen, just colored bars telling you a story about market vibes. Alert come standard to signal those potential bottom or top bars based on the VIX being at your preferred extreme levels.
In essence, "VIX Bars" is like having a volatility radar on your chart. It doesn't make predictions, but it sure gives you a neat, color-coded heads-up on market sentiment. Great for adding an extra dimension to your analysis without getting all tangled up in complex indicators!
vol_rangesThis script shows three measures of volatility:
historical (hv): realized volatility of the recent past
median (mv): a long run average of realized volatility
implied (iv): a user-defined volatility
Historical and median volatility are based on the EWMA, rather than standard deviation, method of calculating volatility. Since Tradingview's built in ema function uses a window, the "window" parameter determines how much historical data is used to calculate these volatility measures. E.g. 30 on a daily chart means the previous 30 days.
The plots above and below historical candles show past projections based on these measures. The "periods to expiration" dictates how far the projection extends. At 30 periods to expiration (default), the plot will indicate the one standard deviation range from 30 periods ago. This is calculated by multiplying the volatility measure by the square root of time. For example, if the historical volatility (hv) was 20% and the window is 30, then the plot is drawn over: close * 1.2 * sqrt(30/252).
At the most recent candle, this same calculation is simply drawn as a line projecting into the future.
This script is intended to be used with a particular options contract in mind. For example, if the option expires in 15 days and has an implied volatility of 25%, choose 15 for the window and 25 for the implied volatility options. The ranges drawn will reflect the two standard deviation range both in the future (lines) and at any point in the past (plots) for HV (blue), MV (red), and IV (grey).
Chandelier ExitChandelier Exit (CE) is a volatility-based indicator developed by "Chuck Le Beau", ATR is used to measure the Volatility.
It identifies stop loss exit points for long and short trading positions.
Configuring the ATR period = 1 and Multiplier = (say) 1.25 or 1.5, it can be used for readily available buffer Stop Loss value from previous high/low.
